Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

This comprehensive dataset curated by Stocksphi presents the 1-minute interval historical stock data for Apple Inc. (AAPL) spanning from 2006 to 2024. The dataset encapsulates key metrics such as opening price, high price, low price, closing price, adjusted close price, and trading volume for each minute of trading throughout this extensive period.

Insights and Applications:

Intraday Analysis: Delve into the intricate price movements and trading dynamics of AAPL stock on a minute-by-minute basis, gaining insights into short-term trends and patterns. Algorithmic Trading: Utilize the dataset to develop and backtest algorithmic trading strategies tailored for intraday trading, leveraging historical price and volume data. Quantitative Analysis: Conduct quantitative analysis to explore statistical properties, correlations, and anomalies within the dataset, facilitating data-driven decision-making. Financial Modeling: Employ the dataset for constructing predictive models and forecasting AAPL stock behavior at a fine-grained temporal resolution. Academic Research: Serve as a valuable resource for academic research in finance, enabling scholars to investigate market microstructure, liquidity dynamics, and other relevant topics. This meticulously curated dataset offers a wealth of information and opportunities for quantitative analysis, strategy development, financial research, and more, empowering traders, analysts, researchers, and enthusiasts to unlock valuable insights and enhance their understanding of AAPL stock dynamics over nearly two decades.

About Dataset:

This dataset includes the daily historical stock prices for Google (GOOGL) spanning from 2020 to 2025. It features essential financial metrics such as opening and closing prices, daily highs and lows, adjusted close prices, and trading volumes. The information offers valuable insights into the stock's performance over a five-year timeframe.

Column Descriptions:

• Price: Date of the stock data (needs cleaning as the first two rows are headers).
• Adj Close: Adjusted closing price, accounting for events like dividends and splits.
• Close: Closing price of the stock at the end of the trading day.
• High: Highest price of the stock during the trading day.
• Low: Lowest price of the stock during the trading day.
• Open: Opening price of the stock at the start of the trading day.
• Volume: Number of shares traded during the day.

What Can You Achieve and Apply on This Data:

• Time Series Analysis: Examine trends and patterns over time.
• Stock Price Prediction: Use machine learning models to forecast future prices.
• Volatility Analysis: Measure the stock's price fluctuations.
• Technical Analysis: Calculate indicators like moving averages, RSI, and MACD.
• Correlation Analysis: Investigate the relationship between volume and price changes.
• Investment Strategy Backtesting: Test trading strategies like moving average crossovers.

Note: 1. This data is scraped from Yahoo Finance by me using python code. 2. Some of the About Data is generated from AI, but verified from me.

Context

Take a look at historical stock prices of major social media companies.

Content

Meta (Facebook), Twitter, Snap, Pinterest and Etsy historical stock prices.

2084Collective/deepstock-stock-historical-prices-dataset-processed dataset hosted on Hugging Face and contributed by the HF Datasets community

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Historical data of the Taiwan Stock Exchange Weighted Index

Complete historical financial dataset for Boston Scientific Corporation

Complete historical financial dataset for Adobe Inc.

Argentina's main stock market index, the Merval, rose to 3060289 points on December 1, 2025, gaining 1.12% from the previous session. Over the past month, the index has declined 1.42%, though it remains 33.32% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Argentina. Argentina Stock Market (MERVAL) - values, historical data, forecasts and news - updated on December of 2025.

Revelyst stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

This table contains 30 series, with data for years 1900 - 1979 (not all combinations necessarily have data for all years), and was last released on 2000-02-19. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Industries (30 items: Manufacturing industries; food and beverage; Clothing and knitting mills; Textile products industries; Tobacco; rubber; primary metals; electrical; non-metallic mineral; petroleum and coal and miscellaneous manufacturing industries ...).

Spain's main stock market index, the ES35, rose to 16493 points on December 2, 2025, gaining 0.63% from the previous session. Over the past month, the index has climbed 2.84% and is up 38.90% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Spain. Spain Stock Market Index (ES35) - values, historical data, forecasts and news - updated on December of 2025.

Complete historical financial dataset for Alphabet Inc.

Complete historical financial dataset for ConocoPhillips

Complete historical financial dataset for Oracle Corporation

Description: This dataset contains 24 years of historical stock data for ITC Limited, a leading Indian multinational conglomerate engaged in businesses such as FMCG (Fast-Moving Consumer Goods), hotels, paperboards, and agri-business. The data spans from [start year] to [end year] and includes daily stock metrics such as opening price, closing price, high, low, volume, and more, providing a comprehensive view of ITC's performance in the National Stock Exchange (NSE).

Context: The dataset offers valuable insights into the long-term trends, volatility, and trading patterns of ITC stocks, facilitating quantitative analysis and investment research. Researchers, analysts, and investors can leverage this dataset to conduct historical performance analysis, develop trading strategies, and make informed investment decisions related to ITC Limited.

Sources: The dataset is sourced from reliable financial data providers and publicly available stock market archives. The data undergoes rigorous validation and cleaning processes to ensure accuracy and consistency, providing users with reliable information for their analyses.

Inspiration: The creation of this dataset was inspired by the growing interest in quantitative finance, stock market analysis, and algorithmic trading within the data science community. By making this dataset available on platforms like Kaggle, we aim to empower researchers, data scientists, and enthusiasts to explore the dynamics of ITC's stock performance and contribute to the advancement of financial analytics and investment strategies.

• Data from Dec 1989 to Dec 2020.
• Includes Income Statement, Balance Sheet, and Cashflow statement.
• Adjusted for restatements.
• Includes valuation metrics such as enterprise valuation and market capitalization.
• Over 30 ratios such as p/e ratio, EBITDA/sales, gross margin etc..
• Standardized categories for comparison between companies.